Some of research contributions based on the SPYRIT toolbox
- The OpenSpyrit ecosystem (Optics Express, 2023)
G. Beneti-Martin, L Mahieu-Williame, T Baudier, N Ducros, "OpenSpyrit: an Ecosystem for Reproducible Single-Pixel Hyperspectral Imaging," Optics Express, Vol. 31, No. 10, (2023). DOI.
- ISTE Book Chapter (ISTE, 2022)
(French) N Ducros. Une introduction à l’imagerie computationnelle monodétecteur. DOI.
(English) N Ducros. In press
- Denoised Completion Network (DC-Net) (Optics Express, 2021)
Antonio Lorente Mur, Pierre Leclerc, Françoise Peyrin, Nicolas Ducros. "Single-Pixel Image Reconstruction from Experimental Data Using Neural Networks," Vol. 29, No. 11, DOI. PDF.
- Completion Network (C-Net) (ISBI, 2020)
Nicolas Ducros, A Lorente Mur, F. Peyrin. "A Completion Network for Reconstruction from Compressed Acquisition." 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), Apr 2020, Iowa City, United States, pp.619-623. DOI. PDF.
Some of educational material based on the SPYRIT toolbox
L Amador, E Chen, N Ducros, H-J Ling, K Mom, J Puig, T Grenier, E Saillard. Hands-on session 4. Deep Learning for Medical Imaging School 2023.
N Ducros, T Leuliet, A Lorente Mur, L Friot--Giroux. Hands-on session 3.1. Deep Learning for Medical Imaging School 2021.
Tutorials to simulate data, reconstruct and train a reconstruction network. It covers different measurement types (linear, Hadamard split), reconstruction networks (pinvNet, DCNet, unrolled proximal gradient descent), and denoising networks (CNN, UNet, DRUNet).